FengheTan9/Multi-Level-Global-Context-Cross-Consistency

Official Pytorch Code base for "Multi-Level Global Context Cross Consistency Model for Semi-Supervised Ultrasound Image Segmentation with Diffusion Model"

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Experimental

This project helps medical professionals, like radiologists or sonographers, more accurately identify and outline abnormalities in ultrasound images, such as tumors in breast or thyroid scans. It takes your existing ultrasound images, including a small set with expert-drawn outlines, and generates more detailed segmentations. This ultimately assists in computer-aided diagnosis by providing clearer boundaries for lesions of varying shapes and sizes.

No commits in the last 6 months.

Use this if you need to improve the accuracy of segmenting lesions in ultrasound images, especially when you have limited labeled data for training.

Not ideal if you are working with medical image types other than ultrasound, or if you do not have any pre-existing labeled ultrasound images.

ultrasound-imaging medical-diagnosis image-segmentation radiology diagnostic-imaging
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 3 / 25

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Stars

39

Forks

1

Language

Python

License

MIT

Last pushed

Jul 18, 2023

Commits (30d)

0

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